docs: def get_mean(self, grp=None):
          """
          Compute the mean curve as a ProbabilityMap
  
          :param grp:
              if not None must be a string of the form "grp-XX"; in that case
              returns the mean considering only the contribution for group XX
          """
          self.init()
          if len(self.weights) == 1:  # one realization
              # the standard deviation is zero
              pmap = self.get(0, grp)
              for sid, pcurve in pmap.items():
                  array = numpy.zeros(pcurve.array.shape[:-1] + (2,))
                  array[:, 0] = pcurve.array[:, 0]
                  pcurve.array = array
              return pmap
          else:  # multiple realizations
              dic = ({g: self.dstore['poes/' + g] for g in self.dstore['poes']}
                     if grp is None else {grp: self.dstore['poes/' + grp]})
              pmaps = self.rlzs_assoc.combine_pmaps(dic)
              return stats.compute_pmap_stats(
                  pmaps, [stats.mean_curve, stats.std_curve],
                  self.weights, self.imtls)